Abstract
To obtain the insight in a single large graph and to save the space consumption for graph mining, the graph summary transforms the input graph into an aggregated concise super-graph represented by supernodes and superedges. In this paper, we investigate current algorithms of the graph summary and aggregation. We provide the classification of them in terms of partition criterion or information lossless. Further, the main graph summary algorithms are compared and discussed in detail. In the end, we give the challenges and future works.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Aggarwal, C., Wang, H.: Managing and Mining Graph Data. Springer, New York (2010)
Chakrabarti, D., Faloutsos, C.: Graph mining: laws, generators, and algorithms. ACM Comput. Surv. 38(1), 2 (2006)
Leskovec, J., Kleinberg, J., Faloutsos, C.: Graphs over time: densification laws, shrinking diameters and possible explanations. KDD’05: Proceedings of the 11th ACM SIGKDD, pp. 177–187. ACM, New York (2005)
S. Navlakha, R. Rastogi, and N. Shrivastava. Graph summarization with bounded error. In: Proceedings of the 2008 ACM-SIGMOD International Conference Management of Data (SIGMOD’08), Vancouver, Canada, pp. 419–432, June 2008
Adler, M., Mitzenmacher, M: Towards compressing web graphs. In: Data Compression Conference, pp. 203–212 (2001)
Boldi, P., Vigna, S.: The webgraph framework i: Compression techniques. In: WWW, pp. 595–602 (2004)
Suel, T., Yuan, J.: Compressing the graph structure of the web. In: Data Compression Conference, pp. 213–222 (2001)
Raghavan, S., Garcia-Molina, H.: Representing the webgraphs. In: ICDE, pp. 405–416 (2003)
Toivonen, H., et al.: Compression of weighted graphs. In: Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM (2011)
Zhou, F.: Methods for network abstraction. University of Helsinki, Helsinki (2012)
LeFevre, K., Terzi, E.: GraSS: graph structure summarization. In: SDM 2010, pp. 454–465 (2010)
Liu, Z., Yu, J.X.: On summarizing graph homogeneously. In: Database Systems for Advanced Applications, pp. 299–310 (2011)
Liu, Z., Yu, J.X., Cheng, H.: Approximate homogeneous graph summarization. JIP 20(1), 77–88 (2011)
Yin, D., Gao, H., Zou, Z.: A novel efficient graph aggregation algorithm. J. Comput. Res. Devel. 48(10) (2011)
Tian, Y., Hankins, R.A., Patel, J.M.: Efficient aggregation for graph summarization. In: Proceedings of the 2008 ACM-SIGMOD International Conference Management of Data (SIGMOD’08), pp. 567–580, Vancouver, Canada, June 2008
Tian, Y., Patel, J.M.: Interactive graph summarization. In: Yu, P.S., Han, J., Faloutsos, C. (eds.) Link Mining: Models, Algorithms, and Applications, pp. 389–409. Springer, New York (2010)
Chen, C., Yan, X., Zhu, F., Han, J., Yu, P.S.: Graph OLAP: towards online analytical processing on graphs. In: ICDM, pp. 103–112 (2008)
Li, C., Yu, P.S., Zhao, L., Xie, Y., Lin, W.: InfoNetOLAPer: integrating InfoNetWarehouse and InfoNetCube with InfoNetOLAP. PVLDB 4(12), 1422–1425 (2011)
Qu, Q., Zhu, F., Yan, X., Han, J., Yu, P.S., Li, H.: Efficient topological OLAP on information networks. In: DASFAA’11, Hong Kong, pp. 389–403, April 2011
Li, C., Zhao, L., Tang, C.J., Chen, Y., et al.: Modeling, design and implementation of graph OLAPing. J. Softw. 22(2), 258–268 (2011)
Zhao, P., Li, X., Xin, D., Han, J.: Graph cube: on warehousing and OLAP multidimensional networks. In: SIGMOD’11, 12–16 June 2011
Zhang, N., Tian, Y., Patel, J.M.: Discovery-driven graph summarization. In: 2010 IEEE 26th International Conference on Data Engineering (ICDE). IEEE (2010)
Rodrigues, J.F., Triana, J.M., Faloutos, C., Triana Jr., C.: SuperGraph visualization. In: Proceedings of the 8th IEEE International Symposium on Multimedia, pp. 227–234 (2006)
Acknowledgments
This work is supported by the Natural Science Foundation of Yunnan Province, China (2010ZC030) and is partially done when the author(s) visited Sa-Shixuan International Research Centre for Big Data Management and Analytics hosted in Renmin University of China. This Center is partially funded by a Chinese National “111” Project “Attracting International Talents in Data Engineering and Knowledge Engineering Research”.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
You, J., Pan, Q., Shi, W., Zhang, Z., Hu, J. (2013). Towards Graph Summary and Aggregation: A Survey. In: Zhou, S., Wu, Z. (eds) Social Media Retrieval and Mining. Communications in Computer and Information Science, vol 387. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41629-3_1
Download citation
DOI: https://doi.org/10.1007/978-3-642-41629-3_1
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-41628-6
Online ISBN: 978-3-642-41629-3
eBook Packages: Computer ScienceComputer Science (R0)